Dr. John-Jose Nunez is conducting research at BC Cancer using artificial intelligence (AI) to predict patient need for psychosocial services such as psychiatry and counselling. The psychiatrist, who is conducting research at BC Cancer, completed his Masters in computer science. His thesis demonstrated the ability to use Natural Language Processing (a form of AI) to predict need for psychiatric consultation from a single oncologist new assessment with 87 per cent accuracy.
He uses artificial intelligence to analyze oncologist clinical dictations to find clues that a patient may be experiencing depression or anxiety and might benefit from psychosocial services. During an initial consultation, physicians and patients often focus much of the appointment on cancer treatment options and don’t always have the opportunity to discuss the many other services that BC Cancer provides to support patients in their journey. It can also be challenging to identify depression and anxiety.
On average, cancer patients with significant depression and anxiety do not survive as long as patients who do not have significant depression and anxiety. This is not because depression or anxiety can cause cancer or make cancer worse - there is considerable evidence against that commonly held belief. More likely, this is because people with significant depression or anxiety have more difficulty following through with recommended cancer treatments and/or tolerating treatment side effects.
It is hoped that in the future, BC Cancer will be able to use artificial intelligence to find patients with psychosocial needs as early as possible and offer them supportive care to reduce their psychological distress and support them to have the best possible outcomes.
Dr. Nunez is a recipient of the 2022/23 UBC Institute of Mental Health Marshall Fellowship
. With additional funding from the BC Cancer Research Institute, Dr. Nunez will be able to expand on this research and is partnering with the UBC Mood Disorders centre on a project that would apply AI to data from patients' smartphones to predict recurrence of depression in order to facilitate early intervention.